By simulating game playing with neural networks, and by using human subjects, it is demonstrated that the interaction between two players in a game of Paper, Rocks and Scissors can give rise to emergent properties that are not inherent in the individual players.

Allen Newell laid down highly influential principles for the study of cognition with his Systems Levels framework, but it is less well known that this framework also laid down the foundation for understanding social interaction and culture. Although his book Unified Theories of Cognition was focused on the cognitive level, Newell speculated what implications his theory might have for the study of culture. Although these particular ideas did not receive much attention at the time, this paper argues that Newell’s systems levels provide a valuable insight into the connection between brains and culture.

A model of humans playing the simple game of Paper Rock Scissors based on the ACT-R architecture (Anderson, 1993; Anderson & Lebiere, 1998) is presented. This model stores in long-term memory sequences of moves and attempts to anticipate the opponent's moves by retrieving from memory the most active sequence. This results in a tightly linked dynamical system in which each player drives the play of its opponent. The performance of this model as a function of the length of the sequences stored and the amount of noise in the system is investigated, and is compared to the performance of human subjects.

Dennett’s (1981) call to use computational frameworks in philosophical analysis can assist in clarifying the distinction between System-1 and System-2 metacognition. Metacognition has been described as “cognition about cognitive phenomena” (Flavell, 1979) and is renowned for its particularly difficult issues. Understanding its “mysterious mechanisms” (Brown, 1987) has been obscured by the subject’s abstractness and disputed terminology. Computation is uniquely suited to overcome these barriers as it forces definitional clarity. New research is supportive of the Common Model of Cognition as the best candidate for computationally modeling the functional organization of the human brain (Stocco et al., 2021). The Common Model represents a powerful tool for investigating unresolved cognitive issues as it is informed by a convergence of research and is well-defined. We propose that applying the Common Model as a philosophical tool can assist in clarifying the problematic distinction between System-1 and System-2 metacognition.